BIVARIATES MEASURES

BIVARIATES MEASURES

1. regression and correlation analysis

   • includes the analysis of sample data to find out how two or more variables in a population are related to each other
   • regression analysis
     • regression analysis gives rise to a mathematical equation that allows us to describe the relationship between two variables, that is, to obtain an ideal line known as the regression line

2. linear correlation

   • tries to establish the relationship or dependency that exists between the two variables involved in a two-dimensional distribution
   • correlation types
     • direct correlation
       • occurs when one of the variables increases, the other increases, the line corresponding to the cloud of points of the distribution is an increasing line
     • inverse correlation
       • occurs when one of the variables increases and the other decreases, the line corresponding to the cloud of points of the distribution is an increasing line
     • null correlation
       • occurs when there is no dependency of any kind between the variables in that case the variables are said to be uncorrelated and the cloud of points has a rounded shape
   • correlation coefficient
     • presents two properties that establish the nature of a relationship between two variables, one is its sign (+0-) and the other is its magnitudepresents two properties that establish the nature of a relationship between two variables, one is its sign (+0-) and the other is its magnitude

3. simple linear regression

   • comprises the attempt to develop a straight line or linear mathematical equation that describes the relationship between two variables

4. Dispersion diagram

   • a bivariate distribution that can be represented in a Cartesian plane is represented as both point and pairs of observations, this graphic representation is called a scatter plot or point cloud

5. coefficient of determination R2

   • term used in regression analysis to denote the relative proportion of variance